Machine learning as a design aid for electrical machines

Author:

Hofmann Wilfried

Funder

Forschungsvereinigung Antriebstechnik e.V.

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering

Reference19 articles.

1. Micklitz T, Kranz J, Hofmann W (2020) FVA 858 I „Maschinelles Lernen, Entwurf, Optimierung – Potenziale Maschinellen Lernens für die Auslegung drehender elektrischer Maschinen. FVA-Abschlussbericht

2. Arnoux P‑H, Caillard P, Gillon F (2015) Modeling finite-element constraint to run an electrical machine design optimization using machine learning. IEEE Trans Magn. https://doi.org/10.1109/TMAG.2014.2364031

3. Bhosekar A, Ierapetritou M (2018) Advances in surrogate based modeling, feasibility analysis, and optimization—A review. Comput Chem Eng 108: 250–267

4. Bramerdorfer G et al (2014) Using FE calculations and data-based system identification techniques to model the nonlinear behavior of PMSms. Ieee Trans Ind Electron 61(11):6454–6462

5. Bramerdorfer G, Zavoianu A‑C et al (2015) Speed improvements for the optimization of electrical machines—a survey. In: IEEE Internat. Electric Machines & Drives Conf. (IEMDC) Coeur d’Alene, 10–13 Mai 2015

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